Function-on-scalar regressionFunctional response modelSmoothingScalar covariateAimThis paper aimed to study the effect of the vaccine on the reproduction rate of coronavirus in Africa from January 2021 to Novem
We propose a novel and robust online function-on-scalar regression technique via geometric median to learn associations between functional responses and scalar covariates based on massive or streaming datasets. The online estimation procedure, developed using the average stochastic gradient descent algorithm,...
In an application to signature verification data, principal coordinate ridge regression, with dynamic time warping distance used to define the principal coordinates, is shown to outperform a functional generalized linear model. Supplementary materials for this article are available online. 2017 American ...
boththeresponsesandthepredictorsarefunctions—whatmightbetermedfunction-on-functionregression;2.theresponsesarescalarsandthepredictorsarefunctions(scalar-on-functionregression);3.theresponsesarefunctionsandthepredictorsarescalars(function-on-scalarregression).Theterms“functionalregression”and“functionallinearmodel”...
Functional regressionFunctional responsegeneralized additive modelsemiparametric regressionpenalized splinesgeophysicsFunction-on-scalar regression models feature a function over some domain as the response while the regressors are scalars. Collections of time series as well as 2D or 3D images can be ...
Functional regressionOracle propertyApplications of functional data with large numbers of predictors have grown precipitously in recent years, driven, in part, by rapid advances in genotyping technologies. Given the large numbers of genetic mutations encountered in genetic association studies, statistical ...
This paper presents a new methodology, called AFSSEN, to simultaneously select significant predictors and produce smooth estimates in a high-dimensional function-on-scalar linear model with a sub-Gaussian errors. Outcomes are assumed to lie in a general real separable Hilbert space, H, while ...
Our framework performs quantile regression and coefficient regularization in a unified manner, allowing them to inform each other and leading to improvement in performance over competing methods, as demonstrated by simulation studies. We also introduce an adjustment procedure to the model to improve its...
Scalar-on-function regression (SoFR) is a suitable regression model in this setting. Most estimation approaches in SoFR assume that the measurement error in functional covariates is white noise. Violating this assumption can lead to underestimating model parameters. There are limited approaches to ...
Function-on-scalar modelsRank regressionB-splinesRobustnessRank regression method has been widely pursued for robust inference in statistical models. Unfortunately, there does not exist related literature for the function-on-scalar model, which is the focus of this paper. We study the robust ...